Alan Schwartz

EnglishCentral

About

Alan Schwartz is CEO & Founder of EnglishCentral. He started his career in Edtech as an English teacher in China over 25 years ago. After that, he spent over a decade in the AI tech industry, including as head of Nuance’s Mobile & Consumer division where he worked with Sony to develop one of the first mobile games using speech technology called Talkman. In 2009, with support from Google Ventures, he founded EnglishCentral, which has become one of the leading conversational platforms for learning English online.

Sessions

Presentation An AI Conversation Partner Integrated with Classroom Learning - Alan Schwartz more

Sun, Jun 14, 11:35-12:00 Asia/Tokyo

This session introduces MiMi Chat, a Gen AI-powered tutor that serves as a conversation partner and provider of formative feedback and assessment, tightly integrated with classroom-based English language curricula. Now used at over 50 universities worldwide, MiMi gives students structured opportunities to practice speaking and receive real-time feedback aligned with CEFR “CAN-DO” goals—outside scheduled class time but directly connected to in-class instruction. Drawing on data from over 15,000 students, we examine measurable gains in speaking output and learner confidence. Case studies include use in a TED-based discussion course, a presentation course, a nursing communication module, and a cross-cultural communication program. We also share engagement metrics, feedback accuracy, and qualitative learner insights.

Alan Schwartz

Presentation Introducing an Open-Source AI-Powered CEFR-Aligned Level Test (OpenALT) more

Sun, Jun 14, 14:35-Mon, Jun 1, 15:00 Asia/Tokyo

The Open AI Level Test (OpenALT) is an open-source English proficiency assessment designed to estimate learners’ levels using the Common European Framework of Reference for Languages (CEFR). The test integrates vocabulary knowledge, listening response, and short conversational interaction to provide a practical estimate of proficiency aligned with CEFR levels and Can-Do descriptors. It consists of three components. First, a vocabulary diagnostic measures receptive lexical knowledge using high-frequency items drawn from the New General Service List (NGSL). Second, a listening-response module evaluates learners’ ability to understand short spoken prompts and produce brief responses. Third, an AI-powered conversational task elicits short spoken or typed responses through a chatbot interface. By combining these components, the test offers an efficient and accessible way to assess communicative ability across CEFR levels.

Alan Schwartz